Specifications using XML Schema Entropy
George Feuerlicht1,2,3, Vladimir Kovar2, David Hartman2, Marek Beranek2, and Pavel Bory2
1University of Technology, Sydney, P.O. Box 123, Broadway, NSW 2007, Australia [email protected]
2Unicorn College, V Kapslovnˇe 2767/2, 130 00 Prague 3, Czech Republic david.hartman,pavel.bory,vladimir.kovar,marek.beranek}@unicorncollege.cz
3Prague University of Economics, W. Churchill Sqr. 4, 130 67 Prague 3, Czech Republic
Abstract. XML schemas are used extensively in e-commerce standardi- zation initiatives. Such XML-based standards define the structure and the semantics of messages that are used to implement business transac- tions in a particular industry domain (e.g. travel). The design of the document structures that form the message payloads is of key impor- tance as once the specification is published it is difficult to re-design the documents without impacting on existing applications. Furthermore, such domain standards need to be maintained and evolved over long time periods, typically decades, without unduly increasing the comple- xity of the specification. The concept of software entropy has been used in the literature to estimate complexity and to express decline in quality, maintainability and understandability of software though its lifetime. In this paper we propose a Message Software Entropy (MSE) metric that estimates the complexity of XML message structures and we use this metric to study the complexity of a subset of the Open Travel Alliance Specification as it evolves over time.
Keywords: complexity metrics, XML schema evolution, software entropy
1 Introduction
XML schemas specifications are used extensively in both vertical domain (e.g.
Open Travel Alliance [1]) and horizontal domain (e.g. ebXML [2]) e-commerce standardization initiatives. Such XML standards define the structure and the se- mantics of messages that are used to implement business transactions in a specific domain of interest (e.g. travel). The messages are typically delivered using SOAP [3] or REST [4] web services, so that in effect the specification forms a basis for a large and complex SOA (Service Oriented Architecture) software system. The design of the document structures that form the message payloads is of key importance as once the specification is published it is difficult to re- design without impacting on existing applications. Furthermore, the longevity
of domain standards requires that the design of the standard documents allows graceful evolution over a very long time period, typically decades, without unduly increasing the complexity of the specification. Many existing standard specifi- cations were designed to overcome the limitations of the Internet as it was at the end of the last century (i.e. high latency, poor reliability and slow response time) rather than with focus on software maintainability and evolution. This typically resulted in specifications consisting of large complex messages suited for stateless communication, but difficult to maintain and evolve. Standard XML specifications (e.g. OTA) typically contain hundreds of complex XML message schemas and thousands of schema elements. As these specifications evolve over time incorporating new requirements their complexity further increases. For example, the OTA message schema that defines the structure of the flight avail- ability requests (OTA AirAvailRQ) contains 428 elements with multiple levels of nesting. Design of such XML schemas typically follows the Document Engi- neering approach [5] or a similar methodology that produces XML documents by aggregating data elements based on pre-defined simple and complex types.
For example, OTA message level schemas are constructed by aggregation of simple (OpenTravel Simple Types) and complex (OpenTravel Common Types, and Industry Common Types) schema elements [1]. This design approach while ensuring uniform structure and semantics of data elements can result in overlap- ping message schemas and excessive complexity, reducing the maintainability of the specification [6].
Evaluation of the quality of the design of XML schema has been the subject of recent research interest. In our previous work we have proposed data coupling metrics that evaluate interdependencies among of a set of XML message schemas by estimating the level of data coupling [7]. In this paper we focus on estimating the complexity of message schemas using the concept of Schema Entropy [8].
In the following section (Section 2) we review related work that addresses the problem of design quality of XML schemas. We then describe our proposal for the Message Schema Entropy (MSE) metric and an XSD Analyzer tool that we developed to compute the MSE metric (Section 3). In Section 4 we present experimental results obtained by analysing OTA Air (Airline) schemas. We note that the OTA message schemas were chosen as an example of open industry domain specifications, and that we do not imply any criticism of the OTA schema design in this work. Section 5 presents our conclusions and outlines directions for further work.
2 Related Work
Evaluation of the quality of design of XML schemas has been the subject of re- cent research interest [9-11]. Ensuring XML schema design quality for industry domain specifications presents a particularly difficult problem as the schemas are often developed in the absence of a domain data model [9]. Current work in this area includes research that focuses on identifying dependencies among schema elements and developing tools for automating the propagation of schema changes
to all dependent components. Necasky, et al. proposed a five-level XML evolu- tion architecture with the top level Platform-Independent Model (PIM) that represents the data requirements for a particular domain of interest. PIM model is mapped into a Platform-Specific Model (PSM) that describes how parts of the PIM schema are represented in XML. PSM then maps into Schema, Operational and Extensional level models. Atomic operations (create, update, and remove) for editing schemas are defined on classes, attributes, and associations, and a mechanism for propagating these operations from PIM to PSM schema is pro- posed. Composite operations are constructed from atomic operations to imple- ment complex schema changes [12-14]. Numerous XML schema quality metrics have been proposed primarily with the objective to measure various aspects of schema complexity. McDowell et al. proposed eleven metrics and two composite indexes to measure the quality and complexity of XML schemas. These met- rics are based on counts of complex type declarations, derived complex types, number of global type declarations, number of simple types, element fanning (fan-out – number of child elements that an element has, andfan-in – number of times that an element is referenced by), etc. [9]. The authors formulate a Quality Index and aComplexity Index that estimate the quality and complexity of XML schemas based on a weighted values of the metrics. A metric analysis tool is provided for developers to verify the validity of the metrics in the con- text of specific projects. The concept of entropy [15] has been adapted to the measurement of complexity of software and was initially applied to procedural software [16] and later to object-oriented design [17,18]. Ruellan [19] used an en- tropy measure to assess the amount of information contained in XML documents (information density) with the objective to reduce the size of XML documents and to improve processing speed of XML messaging applications. Thaw et al.
.[20] proposed entropy-based metrics to measure reusability, extensibility, under- standability of XML schema documents. Basci et al. [11] proposed and validated XML schema complexity metric that evaluates the internal structure of XML documents taking into account various sources of complexity that include re- cursion and complexity arising from importing external schema elements. The authors used the concept of Schema Entropy (SE) to assess XML schema com- plexity. SE is evaluated based on the complexity of schema elements as measured by fan-in and fan-out, and the number of simple elements that constitute indi- vidual schema elements. The SE metric was empirically validated using publicly available XML schemas, and the authors conclude that the metric provides a useful feedback when comparing schemas with equal number of elements [8].
In [21] Tang et al. apply an entropy-based measure to assessing the structural uniformity (structuredness) of XML documents. Two metrics are defined: Path- Based Entropy and Subtree-Based Entropy that attempt to measure the level of diversity of a set of XML documents. Unlike Basci et al. [8,11], the authors base the entropy calculation on XML documents, rather than XML schemas.
Pichler et al. [6] developed a set of metrics to analyse the complexity of business documents with the objective of estimating the effort involved in data element mapping between different business document standards.
Our proposal differs from the above approaches in two important respects.
Firstly, we estimate schema entropy by adapting an entropy-based metric origi- nally developed for object-oriented design [17], and secondly our focus is on the evaluation of the changes in complexity of domain specifications as the specifi- cations evolves over time.
3 Proposed Message Schema Entropy (MSE) Metric
The concept of software entropy has been used in literature to express decline in quality, maintainability and understandability of software though its lifetime.
In our formulation of the Message Schema Entropy (MSE) metric we adapt the Class Definition Entropy (CDE) metric for object-oriented design described in Bansiya et al. [17]. The CDE metric calculates the frequency of occurrence of name strings in a given class. Calculation of MSE metric involves computing the frequency of occurrence of complex schema elements (i.e. schema elements that contains other elements and attributes) using the formulae:
Fig. 1.Fragment of OTA AirAvailRQ schema
MSE =−
N
P
j=1
(Pilog2Pi) where:
N= total number of unique complex elements in the message schema ni = number of occurrences of the ithcomplex element in the message schema
M = total number of non-unique complex elements in the message schema Pi = ni/M
Figure 1 shows a fragment of the schema of the OTA AirAvailRQ message il- lustrating the SpecificFlightInfo element. The OTA AirAvailRQ message is used to implement (web) service for flight availability inquiry and includes 428 ele- ments with multiple levels of nesting. Elements are based on simple types (e.g.
FlightNumber) or on complex types, as is the case with the SpecificFlightInfo ele- ment, which is based on the SpecificFlightInfo Type (extension of SpecificFlight- Info Type). MSE calculation is based on counting complex schema elements (i.e.
elements based on complex types) and represents an approximation, as the in- ternal complexity of individual elements is not taken into account.
3.1 XSD Analyzer Tool
We have developed an XSD Analyzer tool that calculates the values of the MSE.
XSD Analyzer allows the selection of message schemas for analysis and produces an output that includes the total number of non-unique complex schema elements (N1), the number of unique (distinct) complex schema elements (N2), the value of MSE, and counts of occurrences of complex schema elements.
4 Experimental Results
The OTA Air messages are a subset of the OTA specification and are used to implement services that support various business functions related to air- line travel such as checking flight availability, flight booking, etc. For example, the Search and Availability of flights business function is implemented using the Air AvailabilityRQ/RS (request/response) message pair. OTA defines com- mon data types (OTA AirCommonTypes) for the airline messages that form a global type repository of XML Schema components (i.e. simple and complex type definitions) used in the construction OTA Air messages. OTA differentiates betweencomplex types (types that contain multiple data elements) and simple types (types that contain a single data element). We use a subset of OTA Airline (Air) message schemas for our calculations. Open Travel Alliance typically pub- lishes two (A and B) schema specifications each year. We have used air message schema specifications for our evaluation of schema complexity. Table 1 shows MSE values for 26 OTA Air message schemas for versions 2010B to 2013B. The total value of the MSE for the entire set of messages is also shown at the bottom of the tables. It is evident that MSE increases monotonically for all message schemas (with some minor exceptions) as new (enhanced) schema versions are released, indicating that the complexity of the OTA specification is increasing.
The total MSE increases from a value of 143 for the 2010B OTA Specifica- tion to 154 for the 2013B OTA Specification, representing a 7% increase. This increase in MSE over the period of four years is probably not significant and indicates relative stability of the OTA messages schemas. The interpretation of the significance of the MSE values and the increase in MSE as new versions are
released requires further analysis. Some insight into the relative complexity of the message schemas can be gained by comparing the MSE of individual mes- sages schema with the value of MSE computed for the global schema elements (OTA AirCommonTypes) that include all the common elements shared across OTA Air messages. The MSE value for the OTA AirCommonTypes schema for the 2013B version of the OTA Specification equals to 7.55. It can be noted that the MSE value for the some of the message schemas (e.g. OTA AirAvailRQ, OTA AirBookRQ, OTA AirBookRS) exceeds this value, indicating that the com- plexity of these schemas is of similar magnitude as the complexity of the entire
Table 1.Values of MSE for OTA Air Message Schema (Versions 2010B–2013B) OTA Air Message 2010B 2011A 2011B 2012A 2012B 2013A 2013B OTA AirAvailRQ 6.41 6.41 6.41 7.77 7.77 7.77 7.77 OTA AirAvailRS 4.72 4.83 4.83 4.83 4.83 4.83 4.83 OTA AirBookModifyRQ 7.31 7.31 7.32 7.40 7.38 7.35 7.35
OTA AirBookRQ 7.27 7.27 7.27 7.61 7.60 7.56 7.56
OTA AirBookRS 7.32 7.32 7.27 7.67 7.67 7.63 7.63
OTA AirCheckIn 6.41 6.41 6.41 7.04 7.05 7.01 7.01 OTA AirCheckInRQ 6.50 6.50 6.50 7.10 7.10 7.06 7.06 OTA AirCheckInRS 6.56 6.56 6.56 7.13 7.14 7.09 7.09 OTA AirDemandTicketRQ 5.49 5.49 6.56 7.17 7.20 7.18 7.18 OTA AirDemandTicketRS 4.32 4.32 4.32 4.32 4.32 4.32 4.32 OTA AirDetailsRQ 3.55 3.55 3.55 3.55 3.55 3.55 3.55 OTA AirDetailsRS 3.95 4.12 4.12 4.12 4.12 4.12 4.12 OTA AirFareDisplayRQ 5.50 5.50 5.50 6.87 6.87 6.87 6.87 OTA AirFareDisplayRS 6.07 6.07 6.07 6.07 6.07 6.07 6.07 OTA AirFlifoRQ 3.50 3.50 3.50 3.50 3.50 3.50 3.50 OTA AirFlifoRS 3.91 3.91 3.91 3.91 3.91 3.91 3.91 OTA AirLowFareSearchRQ 6.26 6.26 6.22 7.30 7.30 7.30 7.30 OTA AirLowFareSearchRS 6.31 6.31 6.31 7.29 7.29 7.29 7.29 OTA AirPriceRQ 6.36 6.36 6.36 7.15 7.15 7.14 7.14 OTA AirPriceRS 6.27 6.27 6.27 6.27 6.27 6.28 6.28 OTA AirRulesRQ 5.00 5.00 5.00 5.00 5.00 5.00 5.00 OTA AirRulesRS 5.22 5.22 5.22 5.22 5.22 5.22 5.22 OTA AirScheduleRQ 4.30 4.30 4.30 4.30 4.30 4.30 4.30 OTA AirScheduleRS 4.48 4.61 4.61 4.61 4.61 4.61 4.61 OTA AirSeatMapRQ 4.99 4.99 4.99 5.64 5.64 5.64 5.64 OTA AirSeatMapRS 5.14 5.14 5.44 5.97 5.71 5.71 5.71 Total MSE 143.13 143.54 144.83 154.80 154.57 154.31 154.31
global schema. In addition to globally defined schema elements individual mes- sage schemas include locally defined elements that contribute to MSE, explaining this apparent inconsistency.
5 Conclusions and Further Work
Complexity of domain standard specifications is a major factor inhibiting the evolution of specifications and increasing the maintenance costs of domain ap- plications. There is a need for reliable metrics that estimate the complexity of XML-based standard specification and can be used to identify excessively com- plex schema design early in the design cycle. In this paper we have proposed a Message Software Entropy (MSE) metric that estimates the complexity of XML schemas and we have used this metric to study the complexity of a subset of the Open Travel Alliance Specification as it evolves over a period of four years and seven version releases. The results indicate monotonic increase in schema complexity as measured by MSE, with the total MSE increasing from 143 for the 2010B OTA Specification to 154 for the 2013B OTA Specification, representing a 7% increase. This increase is probably not significant and indicates relative stability of the OTA specification. We have also noted that the MSE value for some of the message schemas is of similar magnitude as the value of MSE for the global schema elements OTA AirCommonTypes (7.55), indicating that the com- plexity of these schemas (e.g. OTA AirAvailRQ, OTA AirBookRQ) is similar to the complexity of the entire OTA Air global schema. The current version of the MSE metric is purely based on complex element counts and does not take into account the complexity of the individual elements or the number of levels in the message schema. This makes it easy to interpret the metric, but it also reduces the accuracy of the estimates of schema complexity. MSE metric represents only a first approximation of the complexity of XML schemas, and we are working on refining the MSE metric to take account a range of XML schema structural features.
Acknowledgments. George Feuerlicht wishes to acknowledge the support of Research Centre for Human Centered Technology Design at the Faculty of En- gineering and Information Technology, University of Technology, Sydney, Aus- tralia.
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